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Pega Launches a Unified Solution with AI-Ready APIs

Pega Launches Pega Process Mining with Generative AI-Ready APIs to Enable Continuous Workflow Optimization

Integrated AI-powered capabilities make it easier to continuously find and fix business process inefficiencies

Pegasystems Inc., the low-code platform provider empowering the world's leading enterprises to Build for Change®, announced the launch of Pega Process Mining, which will make it easier for Pega users of all skill levels to find and fix process inefficiencies hindering their business operations. These intuitive process mining capabilities – along with generative AI-ready APIs – will be seamlessly integrated within Pega Platform™, providing organizations with a unified solution to continuously optimize their Pega workflows.

As businesses face increasing customer expectations, process bottlenecks can frustrate both customers and employees. But many process optimization methods and tools are too difficult to use, time consuming to implement, and may not accurately reflect how processes really work. This makes it challenging for organizations to improve their customer and employee experiences, which continue to become more complex over time.

Stemming from last year's acquisition of Everflow, Pega Process Mining uses AI and dedicated algorithms to quickly and accurately model and analyze the 'as-is' lifecycle of their processes based on event log data. It then pinpoints unforeseen bottlenecks, reworks, nonconformances, and other pain points that slow them down – such as extraneous steps in account onboarding processes that takes customers too long to complete. From there, the software will suggest and prioritize more efficient ways for users to refine their processes. This helps businesses accelerate their path to becoming an autonomous enterprise, allowing them to better align their customer journeys to drive higher productivity, reduce costs, and improve experiences.

Powerful yet easy to use
The software's intuitive interface allows citizen developers, business users, and other non-technical staff to take advantage of Pega's highly powerful and scalable process mining capabilities. It avoids complex setup and data preparation by making it simple to quicky feed event log data into the software, which then generates insightful and interactive dashboards to visualize the results. All users – not just experienced data analyst professionals – can dig deeper into the analysis with easy-to-use tools such as root cause analysis to uncover why slowdowns occur; a simulation engine to predict the impact of a proposed process change; and a benchmarking feature to compare how the process has changed over time.

Generative AI-ready capabilities
Pega Process Mining gets even easier to use by connecting it to generative AI models such as OpenAI's ChatGPT via APIs. This enables users to leverage natural language queries to uncover insights about their processes such as "why did our claims process times increase last month in Europe?" or "where are the most urgent bottlenecks in our customer onboarding process that we need to fix?" Pega APIs allow for the use of generative AI models as a front-end interface. Pega will more deeply integrate generative AI capabilities and support in future releases, continuing to make process and task analysis easier to use.

Continuous optimization in one unified platform
By combining Pega Process Mining with Pega Platform, users can continuously build, optimize, and monitor their processes without leaving the Pega environment. Pega users build their application workflows in Pega Platform, the market leading low-code platform for AI-decisioning and workflow automation, and quickly adjust workflows based on recommendations from Pega Process Mining. Users can then easily repeat the process with data from new workflows at any time to monitor the effect of those changes and fix any new bottlenecks that may have emerged. This makes it routine for clients to consistently benefit from their optimization efforts.

Source: Pegasystems media announcement

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